What’s happening this week in economics? - Deloitte

KUALA LUMPUR, 31 JULY 2026 —

Ira Kalish is the chief global economist of Deloitte Services LP. He is a specialist in global economic issues and the effects of economic, demographic, and social trends on the global business environment. First, a quick primer: When investors purchase a security—such as a corporate bond, a government bond, or a collateralized debt obligation—they often want to purchase insurance against the possibility of default.

Currently, an index of CDSs for investment-grade corporate bonds is trading at 53 basis points. Lately, the prices of CDSs issued by many tech companies have risen sharply. Tech companies, many of which are flush with historically high levels of cash, are investing so much in artificial intelligence that they’ve chosen to go to the bond market for financing.

As this has taken place, and as perceived risks have increased, the cost of these CDSs has also risen. There are several potential explanations for the rise in CDS prices. First, there is increasing concern about tech companies’ ability to generate sufficient cash to cover debt-servicing costs. A major tech company reported its first quarter of negative free cash flow since it went public two decades ago.

Moreover, bond yields have risen, and further tightening of monetary policy could push them higher, increasing the cost of servicing debts. Meanwhile, the sharp decline in the equity prices of semiconductor companies could be a signal that investors are concerned about a sharp slowdown in the buildout of AI capacity, which, in turn, could reflect concerns about excess capacity. Second, there is increasing concern in the United States about competition from AI companies in China.

The selloff of tech shares this week was, in part, attributed to concerns about the rise of Chinese AI companies. Many can offer good-quality AI services at relatively low prices. The challenge for US-based AI companies is that the massive investments they are making as first-movers could be undermined by cheaper second-movers—in this case, Chinese companies.

Third, Nikkei Asia reported that the volume of off–balance sheet debt incurred by big tech companies is now large: Off–balance sheet debt had quadrupled in the past four years at five major US-based tech companies, hitting US$1.65 trillion. This is greater than the volume of debt appearing on their balance sheets.

Finally, there is increasing concern about so-called “circular financing.” An example would be where a semiconductor company provides funding to an AI company to build tech capacity. In return, the AI company purchases the semiconductor company’s chips. The main concern with this arrangement is that, if the AI company is unable to generate strong cash flow, it becomes not only a concern for the AI company but also for the semiconductor company.

This is reminiscent of the dot-com bubble 26 years ago when telecom companies invested in internet companies that were buying telecom equipment. When the internet companies had issues, so did the telecom companies. “Technological breakthroughs are typically accompanied by investment booms and buoyant macroeconomic activity. Exuberance about the promise of new technologies intensifies competition among firms eager to capture a share of the revenues.

The race to get ahead can result in excessive investment that makes the boom unsustainable and prone to a disruptive ending. This fragility is further aggravated by the leverage that accompanies the rapid ramp-up of investment. This boom-bust pattern recurs across history, from the US canal mania in the 1830s and the British railway mania in the 1840s, to the roaring ’20s, and the dot-com boom in the late ’90s.

These episodes all ended in sharp corrections, with wider economic fallout.” The Bank for International Settlements goes on to note the massive scale of investment taking place. It said that “the potential demand for AI services is clearly vast and could justify a substantial expansion in computational power.

Yet, relative to its pre-boom trough, the current build-out is on track to outgrow every previous episode only three years in.” It also said that the huge increase in leverage to finance the buildout, along with a lot of circular financing, has increased the risk of potential troubles on the road ahead.

To better understand what could happen, the Bank for International Settlements developed a simple theoretical model, in which, numerous AI firms compete in a “winner take most” environment. With most of the reward from the investment accruing to a small number of players, the end result is excess capacity. Ultimately, “an AI boom creates fragility that undermines itself.

The more capacity the sector builds, the higher the productivity bar it must clear to sustain the boom, so a larger boom is both more likely to disappoint and more damaging when it does.” The Bank for International Settlements concluded that “the larger the boom, the deeper the eventual bust.

The race to commit early through debt and circular financing also makes a bust more likely.” There are three important things to note about this analysis. First, it does not imply that a debilitating correction is likely. It simply implies that such an outcome is a realistic possibility. Second, even if a correction is likely, it is impossible to estimate the timing.

That is, in past episodes, naysayers accurately predicted doom only to find that the doom came much later than anticipated. A boom can go on for a prolonged period before trouble emerges. Third, even if a correction comes, it does not imply that the investments made were foolhardy. It simply implies that the path toward a revolutionary change is not a straight line. There was a sharp correction during the dot-com bubble.

It did not mean that investment in the then burgeoning internet was wrong. After all, the… (AI-assisted rewrite, based on the original source)